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DASCA SDS Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Mathematics and Statistics for Data Science | - Probability and Statistical Inference - Linear Algebra and Optimization |
| Topic 2: Big Data Engineering and Technologies | - Data Pipelines and ETL - Distributed Computing Concepts |
| Topic 3: Artificial Intelligence Applications | - NLP and Computer Vision Overview - Deep Learning Fundamentals |
| Topic 4: Data Management and Governance | - Data Privacy and Security Principles - Data Quality and Lifecycle Management |
| Topic 5: Machine Learning and Predictive Modeling | - Unsupervised Learning - Model Evaluation and Validation - Supervised Learning |
DASCA Senior Data Scientist Sample Questions:
Which of the following is NOT a correct situation to use Agile?
- A. When the final product isn't clearly defined
- B. When changes need to be implemented during the entire process
- C. None of the above
- D. When clients/stakeholders need to be able to change the scope
Correct Answer: C 🗳️
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In unsupervised learning, learning takes place by based on these deductions in input data and developing patterns:
- A. None of the above
- B. Both A and B
- C. Detecting irregularities
- D. Detecting regularities
Correct Answer: B 🗳️
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What is Scrum?
- A. Agile is a subset of Scrum
- B. Scrum and Agile are the same
- C. None of the above
- D. Scrum is a subset of Agile
Correct Answer: D 🗳️
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The grid computing environment uses a middleware to:
- A. Divide computing resources
- B. None of the above
- C. Combine computing resources
- D. Both A and B
Correct Answer: D 🗳️
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Exploratory analytic algorithms help the Data Science team to better:
- A. Understand the data content
- B. Understand patterns in the data
- C. All of the above
- D. Both A and B
- E. Gain a high-level understanding of relationships
Correct Answer: C 🗳️
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